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Kanlet vs Make This Better

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Kanlet compared with Make This Better
DetailKanlet logo KanletMake This Better logo Make This Better
What it doesSemantic context layer that helps AI agents understand your business data accurately Feedback your agent can ship
StageMVP Startup
FoundedNot given Not given
Based inNot given Not given
Pricing modelNot given Freemium
PricingNot given Not given
Key features
  • Connects to 15+ data systems including Snowflake, Databricks, BigQuery, Redshift, dbt, Airflow, Tableau, Looker, Power BI and Postgres
  • Extracts structural metadata including databases, schemas, tables, views, columns and relationship lineage
  • Provides Web-UI, MCP server and REST APIs for accessing semantic context
  • Automatic incremental updates with configurable sync schedules from on-demand to daily or weekly
  • Role-level access controls and data classifications including PII, PHI and SPII
  • Only reads metadata without accessing or moving actual data from systems
  • Integrates with quality monitoring tools including Monte Carlo, Anomalo and Bigeye
  • Automatic screenshot and DOM capture
  • AI-powered feedback triage
  • MCP and CLI integration for coding agents
  • Works with Claude Code, Cursor, Windsurf, and Codex
  • Real-time feedback board with progress tracking
  • User notifications when fixes deploy
  • Private boards and custom domains on paid plans
  • Third-party integrations
  • Bring Your Own Key (BYOK) on all plans
What makes it different
  • Eliminates confident AI mistakes by grounding agents in semantic context instead of having them guess from table names
  • Reduces AI token costs and speeds up answers by resolving schema and joins once upstream instead of in each agent query
  • Ensures consistent answers across all agents and teams using the same definitions and business logic
  • Provides complete traceability and auditability of AI decisions with documented context and ownership
  • Closes the gap between fast AI coding and understanding real user needs
  • Captures context that prevents silent churn
  • One-command setup with no configuration needed
  • Brings user testing into the product without dedicated QA
  • Turns scattered user requests into obvious product priorities
Free planNot given Not given
Open sourceNot given Not given
PlatformsNot given Not given
Public APINot given Not given
Community votes00
DR (Domain Rating by Ahrefs)9 +1 (up) since last check54 no change since last check
Trust Flow (Majestic)17
Citation Flow (Majestic)2436
Referring domains (Majestic)2986

4 details filled in for both companies.

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